This is cool. Good to see. Thanx for posting this. If someone is coding some serious math hackery, drill down into the app and you'll often find someone's variant/version of the old IMSL library routines, written - in Fortran - back in the 1960's. Why? Because that code was extensively tested and was deemed trustworthy. And even better - just went to my bookshelves and found it: "Optimization Techniques With Fortran" - James L. Kuester, Joe H. Mize, McGraw-Hill, 1973, ISBN 0-07-035606-8. It's just an awesome book - it's 9inches by 11 inches, 500 pages chock full of detailed explanations of many of the state-of-the-art circa 1973 optimization techniques for search methods, linear and quadratic programming tricks, least-squares (linear and non-linear methods), dynamic programming (a math technique for making a series of interrelated decisions), and so on. The book has code, examples and detailed explanations - with numerical examples - and flowcharts even, to explain exactly how the code works, and what the program is actually doing. And its all Fortran - some of it IBM/360 Fortran - all in Courier font that's easy to read and use. I had a client that just typed in all the code for a Simplex LP program, and used it to construct a big optimization solution for how to structure the re-investment actions of a large bond portfolio in a treasury department of a big organization.

Before there were neural networks and image-hacking, there was the gritty math-hacking to optimize big gobs of interrelated stuff that had to happen in the right order. It was almost always done in Fortran, and I suspect a lot of it still is. (And if it was not done in Fortran, it was done in APL. Ask an Actuarial scientist, if you doubt this..) Please don't laugh at Fortran. It can not only help you fly your spaceship to another planet (and get you home again!), it can also make you (and your client) rich, since you can build solid, bulletproof code from those old libraries that just works, and hence create flaw-free solutions to really critically important applications. This proposed extension looks useful.

https://github.com/wch/r-source/search?l=fortran&p=1

(https://github.com/wch/r-source says that's 23% of the source. It includes vendored libraries, like a 5MB .f of LAPACK code. I bet a lot of the C code in R was f2c'd at some point in the past)

Similarly, scipy is 18% FORTRAN (jumpy is 0.01% so I didn’t think to link it.)

https://github.com/scipy/scipy